Easily implementable time series forecasting techniques for resource provisioning in cloud computing

Autor:	Fliess, Michel, Join, Cédric, Bekcheva, Maria, Moradi, Alireza, Mounier, Hugues
Rok vydání:	2019
Předmět:	Computer Science - Distributed Parallel and Cluster Computing
Druh dokumentu:	Working Paper
Popis:	Workload predictions in cloud computing is obviously an important topic. Most of the existing publications employ various time series techniques, that might be difficult to implement. We suggest here another route, which has already been successfully used in financial engineering and photovoltaic energy. No mathematical modeling and machine learning procedures are needed. Our computer simulations via realistic data, which are quite convincing, show that a setting mixing algebraic estimation techniques and the daily seasonality behaves much better. An application to the computing resource allocation, via virtual machines, is sketched out. Comment: 6th Conference on Control, Decision and Information Technologies (CoDIT 2019), April 2019, Paris
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1903.02352 Zobrazit plný text záznamu View this record from Arxiv